KeywordHealth Information Management
Electrical and Electronic Engineering
Computer Science Applications
Journal titleIEEE Journal of Biomedical and Health Informatics
Publication Begin page3103
Publication End page3110
MetadataShow full item record
AbstractParkinson's Disease is a disorder with diagnostic symptoms that include a change to a walking gait. The disease is problematic to diagnose. An objective method of monitoring the gait of a patient is required to ensure the effectiveness of diagnosis and treatments. We examine the suitability of Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) Models compared to Symbolic Regression (SR) using genetic programming that was demonstrated to be successful in previous works on gait. The XGBoost and ANN models are found to out-perform SR, but the SR model is more human explainable.